Language Mining: Analysis of the innovation of dominant product languages in design-intensive industries

The main objective of this article is to propose an interpretive model that attempts to decipher a product’s values in terms of functionality, usability and meaning. This model can support companies in better integrating these values in their product offering and in defining the most adequate innovation strategies that they can adopt. The authors conducted an empirical analysis on more than 450 products from the Italian furniture industry. Moreover, using an interpretative model 50 product signs were mapped (materials, surfaces, colours, etc.) for each product. The obtained database was analyzed via the principal component analysis (PCA) statistical technique with the intent to identify dominant product languages. In fact, interpreting a product language as a set of product signs, the article describes an objective process able to identify dominant product languages as combinations of different product signs. Findings – The interpretive model described in this article represents a first result in itself. In addition, by mapping the dynamics of dominant product languages, it has been demonstrated that they evolve differently in relation to several product typologies. In turn, the possibility of “brokering” dominant product languages from one product typology to another and from one industry to another has been verified. Practical implications – First of all, this model can support companies in the identification of emerging trends and, consequently, allows them to develop product semantic forecasts. In addition, the analysis of dominant product languages over time can also allow a company to propose combinations of product signs typical of past periods. Finally, the identification of dominant product languages can also allow companies to analyze the state-of-the-art of the industry and, consequently, identify different ways to propose innovation to the market.